Random Forest Regressor

This module belongs to the " Machine Learning algorithms" category.

Description

This module is a parameterizable and trainable Random Forest regression model.

It contains functions to variate the sample leaf nodes, impurity, features and depth, just like the Random Forest Classifier.

Parameters

For forecasting accuracy , as criteria of measure, we have the choice between mse (stands for : mean squared error ) and mae (mean absolute error) . (for more details refer to Sci-kit metrics )

whereas features can be :

• auto,

• SQRT

• Log2

• Integer

• Float

• None